Industries providing services involving a complex technical infrastructure, such as the telecommunications industry, are faced with unique challenges in meeting customer expectations and maintaining customer satisfaction. For example, a network outage or similar service event may disrupt or otherwise impair telecommunication services, thereby impacting customer satisfaction. To identify potential service events, alarms are often utilized to prompt resolution. Conventional methods manually investigate and address such alarms. Services involving complex technical infrastructures, however, can be faced with over one million alarms at any one time. With such a volume of alarms, manually investigating and addressing each alarm expends significant time and resources.
Alarms in the telecommunications industry are often related to network provisioning activities, such as customer ordered disconnects, groom work, and the like, and are thus false alarms in a sense or otherwise easy to resolve. Manually investigating alarms related to provisioning activities is often impeded by a cluster of information in attempting to trace the alarm through the network path to its root cause and to address additional alarms tied to the root cause. However, provisioning issues typically do not directly impact service for current customers and are therefore a lower priority than resolving other network issues. Due to the tremendous resources needed to address all network alarms, lower priority alarms, such as those related to provisioning issues, are often left unaddressed, thereby underutilizing deployed network assets and increasing the volume of alarms.
It is with these observations in mind, among others, that various aspects of the present disclosure were conceived and developed.